A2 Refereed review article in a scientific journal
Digital Biomarkers and AI for Remote Monitoring of Fatigue Progression in Neurological Disorders: Bridging Mechanisms to Clinical Applications
Authors: Rudroff, Thorsten
Publisher: MDPI
Publishing place: BASEL
Publication year: 2025
Journal: Brain Sciences
Journal name in source: BRAIN SCIENCES
Journal acronym: BRAIN SCI
Article number: 533
Volume: 15
Issue: 5
Number of pages: 25
eISSN: 2076-3425
DOI: https://doi.org/10.3390/brainsci15050533
Web address : https://www.mdpi.com/2076-3425/15/5/533
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/498504475
Digital biomarkers for fatigue monitoring in neurological disorders represent an innovative approach to bridge the gap between mechanistic understanding and clinical application. This perspective paper examines how smartphone-derived measures, analyzed through artificial intelligence methods, can transform fatigue assessment from subjective, episodic reporting to continuous, objective monitoring. The proposed framework for smartphone-based digital phenotyping captures passive data (movement patterns, device interactions, and sleep metrics) and active assessments (ecological momentary assessments, cognitive tests, and voice analysis). These digital biomarkers can be validated through a multimodal approach connecting them to neuroimaging markers, clinical assessments, performance measures, and patient-reported experiences. Building on the previous research on frontal-striatal metabolism in multiple sclerosis and Long-COVID-19 patients, digital biomarkers could enable early warning systems for fatigue episodes, objective treatment response monitoring, and personalized fatigue management strategies. Implementation considerations include privacy protection, equity concerns, and regulatory pathways. By integrating smartphone-derived digital biomarkers with AI analysis approaches, the future envisions fatigue in neurological disorders no longer as an invisible, subjective experience but rather as a quantifiable, treatable phenomenon with established neural correlates and effective interventions. This transformative approach has significant potential to enhance both clinical care and the research for millions affected by disabling fatigue symptoms.
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Funding information in the publication:
This research received no external funding.
